In order to inspect pipelines, especially for the transport of oil or gas, it is known to use inspection pigs which have specifically sensitive sensors arranged on their outer shell around the periphery thereof. Using these sensors, the condition of the pipeline is sensed, and can thereby be verified. Sensors that are suitable for this purpose are based on different physical principles. Known sensors include, for example, piezoelectric, electro-acoustic, magnetic sensors, and the EMAT sensors mentioned above.
The measured data obtained by the sensors is converted into electrical analog signals and digitized in an analog-to-digital converter for further processing/use. During a run through a long oil/gas pipeline, tremendous amounts of data are generated. During such a run, such a pig is not connected to the outside world. Therefore, the generated data must be stored in a form that allows the wall condition to be reconstructed outside the pipeline after the run, allowing abnormalities/damage/defects of/to the pipe wall to be located and reliably quantified. In the case of direct (1:1) data storage, even modern memories will overflow. Therefore, the digital data generated from the analog values must be reduced/compressed in a way that will ensure the reconstruction stipulated hereinabove. Qualitatively, this means that there is no need to store data of inconspicuous/sound areas of the pipe wall. Thus, in the detection of damage in walls of long/very long pipelines, data reduction methods are used to extract the essential features of a signal associated with a defect in the pipe wall, and to represent said features as accurately as possible with a minimum number of bits to thereby reduce/minimize the amount of data to be stored.
The amplitude-transit time-position curve (ALOK) method (O. A. Barbian, B. Grohs, R. Licht, “Signalanhebung durch Entstörung von Laufzeit-Messwerten aus Ultraschallprüfungen von ferritischen und austenitischen Werkstoffen—ALOK”, Teil 1. Materialprüf. 23 (1981) 379-383) [Signal enhancement by suppressing noise in transit time measurement data from ultrasonic inspection of ferritic and austenitic materials—ALOK”, part 1, Materials Testing, Vol. 23, (1981), pp. 379-383] selects the peaks of the ultrasound envelope. This makes it possible to achieve a high reduction factor. However, essential information is lost from the signal during reduction. For example, the stored data does not provide any information about the shape of the ultrasonic reflection or about the background in the region of the selected vectors. However, this information is very important for determining the structure and size of the defect. Moreover, peak structures in the noise are selected as being worthy to be stored, thus worsening the reduction factor.
German Patent DE 4040 190 describes a method in which the amplitude maximum and the time value are stored when a predetermined threshold is no longer met. However, the method does not analyze the width and characteristic of the envelope. In addition, the method requires an ultrasonic signal that is smoothed by a low-pass filter.
In EMAT technology, an EMAT probe including an EMAT transmitter and an EMAT receiver produces an ultrasonic wave train (US wave train) in the pipe/pipeline wall by electrical/magnetic forces, said ultrasonic wave train having a predetermined number of wavelengths, preferably 5-10 wavelengths. This wave train propagates through the pipeline wall and is reflected at interfaces. The reflected US wave is detected by the EMAT receiver and converted back into a proportional electrical signal (see GB 2 380 794 A). The transmitter can send single pulses and waves of different shape and frequency, depending on the waveform generator incorporated therein. Sensors typically used have transmitter frequencies between about 400 kHz and about 2 MHz. The data of the electromagnetic sensors are recorded at a resolution of 12-16 bits and at a sampling rate of, for example, 20 MHz, using analog-to-digital (AD) converters. For an inspection pig having 50 sensors which are at least partially operated in multiplex mode, and an inspection speed of 1 m/sec, about 200 TB of data is typically generated over a pipeline length of 500 km. This data volume must be stored in the traveling pig during the inspection run, because there is no connection to the outside while the pig is moving.
Depending on the microstructure of the steel, the surface structure and the coating of the pipeline, the signal detected by the receiver can vary very strongly even if the steel is free of defects. This leads to fluctuations in the signal background. However, the echo amplitude reflected by a crack in relation to the background is very important for determining the size of the crack.
In order to limit the volume of data to storable amounts and to achieve an economic range for the pig, it is mandatory to perform data reduction.